1. Field of the Invention
The present invention relates to electronic assemblies, more particularly a method and a system for determining whether an electronic assembly is assembled correctly.
2. Description of the Related Art
Because some components of an electronic assembly have polarity, they are required to be assembled in a specific orientation onto a circuit board or a substrate. However, there have been instances in which the components are assembled backwards from the desired orientation. Sometimes the detection of the orientation cannot be readily tested by conventional in-circuit or function product tests, and other tests may be destructive.
A typical non-destructive test relies on visual examination, using a commercially available vision system. Certain commercial vision systems are available whereby a model image having a correct orientation is used to correlate to the actual component being checked. Typically vision correlation algorithms are used to match the pattern of the test electronic assembly with the pattern of the model image. A correlation value of between 0 to 1 may be obtained depending on how close the match is. The value of 0 means the machine cannot find anything that looks like the model image at all. The value of 1 means the machine has found a perfect match. A typical threshold for acceptance of the test electronic assembly might be a value around 0.7.
There are several problems in the process of inspecting electronic components with an automatic vision system. For example, capacitors have a band that marks polarity, but there is also small printing near the band. These markings are not specifically designed for automated vision purposes. The plastic wrap around the part is cut and shrunk around the component. However, the length of the component and the pitch of the printing do not match. Therefore, the wraps that are left around the top of the part may cause the image to vary.
In another example, diodes have a band on one end, and may have printing in the middle with information such as part number of supplier logo. Diodes are often black or grey and their brightness and reflectance can vary. In addition, both caps and diodes may flop or tilt in the holes relative to the circuit board, so the image of the component and board may change from product-to-product.
In checking these components against a fixed image model, a problem occurs due to part variation. The threshold value needs to be set low enough to accommodate the variation, otherwise false rejects will be a problem. If the threshold is set too low, then the possibility of false accepts arises. Vision systems traditionally suffer from being “brittle” whereby small changes in the target image can easily throw off the vision algorithms.